Abstract
Objectives
We analyzed malaria cases and cluster outbreaks in the capital city between 2022 and 2024 to provide baseline data to guide effective prevention and response strategies.
Methods
All malaria cases reported in the Integrated Disease Control Information System between January 1, 2022, and December 31, 2024, were included. Annual trends, demographics, regional distributions, and case clusters were analyzed. Clusters were defined as multiple cases occurring within 14 days and within 1 km of suspected infection sites based on 2024 Malaria management guidelines. Spatial analysis was conducted using QGIS version 3.34.
Results
In 2024, 620 malaria cases were reported in the capital city, representing 94.1% of total cases nationwide. This number represents a slight decrease from 2023, but a 78.7% increase from 2022. A total of 47 case clusters were identified, including five (10.6%) in military units. Clusters were concentrated in high-risk areas near the North Korean border, especially in northwestern Gyeonggi, Ganghwa-gun, and Incheon. Primary risk factors included residence (57.8%), work (12.9%), military service in high-risk areas (12.9%), and outdoor leisure activities including travel and exercise.
Conclusions
The post-coronavirus disease 2019 rise in malaria incidence is linked to resumption of social activities and enhanced surveillance. The capital region remains the focal point of domestic transmission, highlighting the need for regional and population-specific control measures. Targeted strategies for military personnel and outdoor workers are critical to achieve Korea’s national malaria elimination by 2030 goal.
Keywords: Vector borne diseases; Malaria; Malaria, vivax; Cluster analysis
Key messages
① What is known previously?
Malaria, mainly caused by Plasmodium vivax, shows seasonal outbreaks near border areas, with malaria clusters especially prevalent in the northwestern capital region.
② What new information is presented?
In 2024, over 90% of malaria cases occurred in the capital region, with 47 clusters in Gyeonggi. Major risks include residence or work in high-risk areas and nighttime outdoor activities including sports, camps, short-term visit, fishing, and military service.
③ What are implications?
The Capital Regional Center for Disease Control and Prevention should apply stricter cluster criteria and detailed surveys for monitoring and response. Early detection, prevention, and tailored regional management are key to malaria re-elimination.
Introduction
Malaria is an acute febrile infectious disease transmitted by female Anopheles mosquitoes that carry protozoa of the Plasmodium genus (including Plasmodium vivax, Plasmodium ovale, Plasmodium malariae, Plasmodium falciparum, and Plasmodium knowlesi). It is classified as a Class III infectious disease in the Republic of Korea (ROK) under the Infectious Disease Control and Prevention Act [1]. According to the World Health Organization (WHO)’s world malaria report 2024, approximately 263 million cases of malaria and 597,000 deaths related to malaria were reported worldwide in 2023, an increase of approximately 11 million cases from that in the previous year and a resurgence following a recent period of stagnation [2].
P. falciparum is considered the predominant causative pathogen of malaria globally and is prevalent in tropical and subtropical regions. In contrast, P. vivax accounts for the majority of malaria cases in ROK, characterized by a relatively mild clinical course and a distinct seasonal pattern [3,4]. In 1979, ROK declared the elimination of malaria in collaboration with the WHO; however, the disease reemerged in 1993, when a case was reported among soldiers in Paju-si, Gyeonggi, near the border with North Korea. As the number of cases continued to increase, the Korea Disease Control and Prevention Agency (KDCA) established the “Second Malaria Re-elimination Action Plan (2024–2028),” aiming to achieve national malaria eradication by 2030 [5]. As of 2025, 49 cities, counties, and districts in the Seoul metropolitan area (including Seoul, Incheon, Gyeonggi, and Gangwon) have been designated and managed as “malaria risk areas” due to their high incidence or potential for transmission from neighboring regions [6].
Most malaria cases in ROK occur in northern Gyeonggi, Incheon, and Seoul, with the main presumed areas of infection reported to be Paju-si and Yeoncheon-gun in Gyeonggi, Ganghwa-gun in Incheon, and the northwestern region of Seoul [4]. This geographical concentration highlights the importance of regional surveillance and response efforts led by the Capital Regional Center for Disease Control and Prevention, which has been responsible for malaria surveillance and cluster response activities since 2024.
The present study limited its scope of analysis in two respects. First, it focused only on domestically transmitted cases, as the national goal of malaria re-elimination in ROK is limited to domestic outbreaks, and cluster investigations are conducted specifically for domestic disease management. Second, only cases from the past 3 years (2022–2024) were analyzed. Data during 2020–2021, the period of the coronavirus disease 2019 (COVID-19) pandemic, were excluded because social distancing measures and the diversion of public health resources toward the COVID-19 response made it difficult to accurately assess malaria trends.
Based on this background and research scope, this study aimed to investigate the incidence and cluster patterns of malaria cases in the Seoul metropolitan area in 2024, and to provide foundational data for developing effective prevention and response strategies in the future.
Methods
1. Study Population
The study population comprised all malaria patients reported in the Integrated Disease Control Information System between January 1, 2022 and December 31, 2024. Patients were classified into three groups: “patients,” “suspected patients,” and “pathogen carriers.” ”Patients” were defined as individuals who exhibited clinical symptoms consistent with malaria and were confirmed to be infected according to diagnostic testing criteria. “Suspected patients” were defined as individuals suspected of having malaria based on clinical symptoms and epidemiological links and presumed to be infected according to presumptive diagnostic criteria. “Pathogen carriers” were defined as individuals without clinical symptoms but confirmed to harbor Plasmodium parasites according to confirmatory diagnostic testing criteria. Recurrent cases were excluded to prevent duplication, and the final analysis was conducted using patient data based on the date of case reporting [6].
Cluster cases were defined according to the 2024 Malaria management guidelines as instances in which the interval between symptom onsets among patients within a malaria-risk area was ≤14 days, and the distance between residences, including the presumed infection area, was ≤1 km [6].
2. Study Content and Methods
Changes in the number of malaria cases in the Seoul metropolitan area were comparatively analyzed using data from the past 3 years (2022–2024). Annual incidence was examined based on the date of case reporting, and analyses by sex, age, and region (patient’s residential address, presumed infection area, etc.) were performed using case reports and epidemiological investigation data. In addition, nine regions accounting for more than 50% of all reported cases were designated as high-case areas and analyzed separately. The incidence rate per 100,000 population (number of patients/resident registration population) in each high-case area was calculated using the 2024 mid-year civil registration population data from the National Population Trend Survey [7]. For the cluster case analysis, Quantum Geographic Information System (QGIS) version 3.34 was used to map patient locations based on residential address. Latitude and longitude coordinates for presumed infection areas were entered using the World Geodetic System 1984 (WGS84; EPSG:4326) coordinate system. Base maps were sourced from maps provided by the Ministry of Land, Infrastructure and Transport’s V-World service. All map creation and spatial analyses were performed within the QGIS environment [8].
Results
1. Current Status of Malaria in the Seoul Metropolitan Area
In 2024, the total number of malaria cases in the Seoul metropolitan area (based on patient residence) was 620, accounting for 94.1% of the 659 cases reported nationwide. Males had a higher incidence (514 cases, 82.9%) than females, and individuals aged 20–29 years showed the highest incidence (194 cases, 31.3%) among all age groups. By region, Gyeonggi reported the greatest number of cases (377, 60.8%), followed by Incheon (128 cases, 20.6%), Seoul (87 cases, 14.0%), and Gangwon (28 cases, 4.5%) (Table 1).
Table 1. Number and proportion of malaria cases in the capital region, 2022–2024.
| Classification | 2024 | 2023 | 2022 | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Case (ratea)) |
Case (ratea)) |
Change from 2024 difference value (rate) | Case (ratea)) |
Change from 2024 difference value (rate) | |||||
| Nationwide | 659 (100.0) | 673 (100.0) | –14 (△2.1) | 381 (100.0) | 278 (73.0) | ||||
| Capital region | Total | 620 (94.1) | 638 (94.8) | –18 (△2.8) | 347 (91.1) | 273 (78.7) | |||
| Gender | Male | 514 (82.9) | 536 (84.0) | –22 (△4.1) | 292 (84.1) | 222 (76.0) | |||
| Female | 106 (17.1) | 102 (16.0) | 4 (3.9) | 55 (15.9) | 51 (92.7) | ||||
| Age (yr) | 0–9 | 2 (0.3) | 5 (0.8) | –3 (△60.0) | 4 (1.2) | –2 (△50.0) | |||
| 10–19 | 20 (3.2) | 30 (4.7) | –10 (△33.3) | 23 (6.6) | –3 (△13.0) | ||||
| 20–29 | 194 (31.3) | 175 (27.4) | 19 (10.9) | 110 (31.7) | 84 (76.4) | ||||
| 30–39 | 94 (15.2) | 110 (17.2) | –16 (△14.5) | 59 (17.0) | 35 (59.3) | ||||
| 40–49 | 99 (16.0) | 104 (16.3) | –5 (△4.8) | 54 (15.6) | 45 (83.3) | ||||
| 50–59 | 96 (15.5) | 115 (18.0) | –19 (△16.5) | 64 (18.4) | 32 (50.0) | ||||
| 60–69 | 71 (11.5) | 62 (9.7) | 9 (14.5) | 23 (6.6) | 48 (208.7) | ||||
| 70–79 | 35 (5.6) | 28 (4.4) | 7 (25.0) | 7 (2.0) | 28 (400.0) | ||||
| 80–89 | 8 (1.3) | 9 (1.4) | –1 (△11.1) | 3 (0.9) | 5 (166.7) | ||||
| ≥90 | 1 (0.2) | 0 (0.0) | 1 (-) | 0 (0.0) | 1 (-) | ||||
| Region | Seoul | 87 (14.0) | 84 (13.2) | 3 (3.6) | 52 (15.0) | 35 (67.3) | |||
| Incheon | 128 (20.6) | 118 (18.5) | 10 (8.5) | 60 (17.3) | 68 (113.3) | ||||
| Gyeonggi | 377 (60.8) | 410 (64.3) | –33 (△8.0) | 223 (64.3) | 154 (69.1) | ||||
| Gangwon | 28 (4.5) | 26 (4.1) | 2 (7.7) | 12 (3.5) | 16 (133.3) | ||||
Unit: n (%). △=decrease. a)Cases/total casess of the category.
The total number of malaria cases in the capital region in 2024 (n=620) had decreased by 18 cases (2.8%) compared with the 638 cases in 2023 but increased by 273 cases (78.7%) compared with the 347 cases in 2022. However, given that the COVID-19 pandemic extended into 2022, these trends should be interpreted with caution. By region, Gyeonggi reported 377 cases, a decrease of 33 cases (8.0%) from the 410 cases in 2023. In contrast, Seoul (87 cases) showed an increase of three cases (3.6%), Incheon (128 cases) an increase of 10 cases (8.5%), and Gangwon (28 cases) an increase of two cases (7.7%) compared with that in the previous year. Although Gyeonggi, which consistently accounts for the largest proportion of malaria cases in the metropolitan area, experienced a decline, Seoul, Incheon, and Gangwon exhibited an upward trend (Table 1).
2. Current Status of Malaria in the High-case Areas of the Seoul Metropolitan Area
In 2024, malaria cases in the Seoul metropolitan area (based on patient residence) were primarily concentrated in the northwestern region, encompassing seven basic local governments or nine when administrative districts are included. By administrative district, six were located in Gyeonggi (Paju-si, Gimpo-si, Ilsanseo-gu in Goyang-si, Deogyang-gu in Goyang-si, Ilsandong-gu in Goyang-si, and Yeoncheon-gun), two in Incheon (Ganghwa-gun and Seo-gu), and one in Gangwon (Cheorwon-gun) (Table 2).
Table 2. Number and proportion of malaria cases in major outbreak areas of the Capital Region, 2022–2024.
| Classification | 2024 | 2023 | 2022 | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Case (ratea)) |
Rateb) | Case (ratea)) |
Change from 2024 difference value (rate) |
Case (ratea)) |
Change from 2024 difference value (rate) |
||||||
| Capital region | 620 (100.0) | [6.7] | 638 (100.0) | –18 (△2.8) | 347 (100.0) | 273 (78.7) | |||||
| High-case area | Total | 380 (61.3) | [13.4] | 394 (61.8) | –14 (△3.6) | 180 (51.9) | 200 (111.1) | ||||
| Gyeonggi | Paju-si | 147 (23.7) | [29.3] | 153 (24.0) | –6 (△3.9) | 57 (16.4) | 90 (157.9) | ||||
| Gimpo-si | 56 (9.0) | [11.6] | 81 (12.7) | –25 (△30.9) | 33 (9.5) | 23 (69.7) | |||||
| Goyang-si | Total | 56 (9.0) | [5.3] | 58 (9.1) | –2 (△3.4) | 44 (12.7) | 12 (27.3) | ||||
| Ilsanseo-gu | 27 (4.4) | [9.5] | 25 (3.9) | 2 (8.0) | 10 (2.9) | 17 (170.0) | |||||
| Deogyang-gu | 15 (2.4) | [3.0] | 16 (2.5) | –1 (△6.3) | 24 (6.9) | –9 (△37.5) | |||||
| Ilsandong-gu | 14 (2.3) | [4.8] | 17 (2.7) | –3 (△17.6) | 10 (2.9) | 4 (40.0) | |||||
| Yeoncheon-gun | 26 (4.2) | [63.4] | 27 (4.2) | –1 (△3.7) | 6 (1.7) | 20 (333.3) | |||||
| Incheon | Seo-gu | 42 (6.8) | [6.7] | 38 (6.0) | 4 (10.5) | 18 (5.2) | 24 (133.3) | ||||
| Ganghwa-gun | 30 (4.8) | [43.5] | 19 (3.0) | 11 (57.9) | 12 (3.5) | 18 (150.0) | |||||
| Gangwon | Cheorwon-gun | 23 (3.7) | [56.3] | 18 (2.8) | 5 (27.8) | 10 (2.9) | 13 (130.0) | ||||
Unit: n (%). a)Cases/total malaria cases in the capital region. b)Person per 100,000 population, [Cases].
Among the nine high-case areas, Paju-si reported the highest number of cases (147, 23.7%), followed by Gimpo-si (56 cases, 9.0%), Ilsanseo-gu (27 cases, 4.4%), Deogyang-gu (15 cases, 2.4%), Ilsandong-gu (14 cases, 2.3%), Seo-gu (42 cases, 6.8%), Ganghwa-gun (30 cases, 4.8%), Yeoncheon-gun (26 cases, 4.2%), and Cheorwon-gun (23 cases, 3.7%) (Table 2).
The incidence rate per 100,000 population in these areas exhibited a different pattern from the absolute number of cases. While Paju-si recorded the highest number of cases, its incidence rate was relatively low. In contrast, Yeoncheon-gun and Cheorwon-gun, despite having fewer cases, showed relatively high incidence rates. These differences reflect regional characteristics such as population size and composition (including military personnel) and should be interpreted with caution, given the associated statistical limitations (Table 2).
3. Current Status of Malaria Cluster Cases and Key Risk Factors in the Seoul Metropolitan Area
In 2024, a total of 47 malaria clusters were reported in the Seoul metropolitan area, of which five (10.6%) were associated with military units. By province and city, Gyeonggi accounted for 39 cases (83.0%), Incheon for six cases (12.8%), and Seoul and Gangwon for one case each (2.1%). At the municipal and district level (including administrative districts), Paju-si reported 22 cases (46.8%), Gimpo-si 12 (25.5%), Seo-gu three (6.4%), and Ilsandong-gu and Ilsanseo-gu two cases each (4.3%) (Figure 1).
Figure 1. Distribution of malaria cluster cases and patients in the capital area, 2024.
Blue dots indicate the distribution of malaria cases based on patients’ residential addresses, and yellow circles represent areas within a 1-km radius from the presumed infection sites of cluster cases. Cluster cases include malaria occurrences within military units (3 cases in Paju-si, one case in Yeoncheon-gun, and one case in Cheorwon-gun).
Most clusters consisted of two patients (35 clusters), while the largest cluster, located in Paju-si, involved six patients. Other clusters included those with five patients (two clusters), four patients (three clusters), and three patients (six clusters).
Among the 47 clusters, one involved a family identified through testing of co-exposed individuals, although the genotypes did not match. Based on social linkages, clusters included five military-related clusters that occurred within the same battalion and three workplace-related clusters associated with outdoor or semi-open work environments (e.g., welding, carpentry, interior work, and logistics centers). Additionally, two clusters were associated with soccer field exposure, one of which involved two individuals diagnosed simultaneously with matching genotypes. Other clusters were linked to outdoor or nighttime bar visits and work (two cases) and camping in high-risk areas (one case).
Analyses of cluster cases using a GIS revealed sporadic occurrences throughout the Seoul metropolitan area. However, when focusing on presumed infection sites, cluster cases were concentrated in high-risk regions such as the northwestern part of Gyeonggi and Ganghwa-gun in Incheon, both located near the North Korean border (Figure 2). This pattern indicates that malaria transmission in ROK is predominantly influenced by border regions with North Korea, as areas along the demilitarized zone (DMZ) form a geographically and ecologically continuous habitat for vector mosquitoes. Research suggests that the persistence of border malaria is primarily driven by shared ecological environments and frequent interactions among people, parasites, and vectors in adjacent regions [9]. Although direct cross-border human movement is limited in ROK, the seasonal migration of mosquito populations and local human activities in North and ROK (such as those involving military personnel, residents, and workers) facilitate pathogen transmission, resulting in epidemiological characteristics typical of border malaria.
Figure 2. Distribution of malaria cases in the capital area, 2024.
(A) Based on patients’ residential addresses. (B) Based on presumed infection sites.
Key risk factors for cluster cases were categorized into “high-risk areas” and “high-risk activities.” Regarding risk areas, residential settings accounted for the largest proportion (67 cases, 57.8%), followed by workplaces and military service, each with 15 cases (12.9%). Among the 67 individuals residing in high-risk areas, 46 cases (68.7%) occurred in peri-urban (mixed rural-urban) zones, 20 cases (29.9%) in urban areas, and one case (1.5%) in rural areas, indicating a tendency for cluster cases to concentrate in peri-urban environments.
High-risk activities included short-term visit or camping (seven cases, 6.0%), sports such as soccer, futsal, or running (six cases, 5.2%), fishing (one case, 0.9%), and agriculture- or livestock-related work (five cases, 4.3%) (Table 3). These findings suggest that while prolonged exposure, such as residence in high-risk areas, remains the primary contributor to malaria transmission, short-term exposures, including recreational or occupational outdoor activities, can also be a contributing factor.
Table 3. Major risk factors among malaria cluster cases in the capital region, 2024.
| Classification | 2024 Case (rate) | ||
|---|---|---|---|
| Capital regiona) | 116 (100.0) | ||
| Risk areas | Living | 67 (57.8) | |
| Working | 15 (12.9) | ||
| Residing in a military unit | 15 (12.9) | ||
| Risk-related activities | Leisure activities | Travel (short-term visit, camping, others) | 7 (6.0) |
| Exercise (soccer, futsal, running, others) | 6 (5.2) | ||
| Fishing | 1 (0.9) | ||
| Agricultural-related activities (farming, livestock, fieldwork, others) | 5 (4.3) | ||
Unit: n (%). a)Includes 15 cases of military patients within the capital region.
Conclusion
This study examined malaria incidence trends in the Seoul metropolitan area from 2022 to 2024, with particular focus on cluster cases that occurred in 2024.
In 2024, a total of 620 malaria cases were reported. Although this represented a slight decrease from the previous year, the metropolitan area still accounted for over 90% of all cases in ROK. This figure also marked a substantial increase compared with 2022, during which the COVID-19 pandemic was ongoing. The observed increase may reflect the combined effects on malaria management resulting from travel restrictions, social stigma, and reallocation of health resources and policy priorities toward pandemic response efforts [10]. These findings suggest that social changes and the restoration of surveillance systems can significantly influence malaria incidence trends, underscoring the need for cautious interpretation.
Furthermore, the number of cases, which represents the absolute scale of malaria, was used as the primary indicator for analysis and was supplemented by the incidence rate, which reflects disease severity relative to population size. While Paju-si recorded the highest total number of cases, Yeoncheon-gun and Cheorwon-gun showed higher incidence rates relative to their population sizes. Therefore, both case counts and incidence rates should be considered concurrently to accurately interpret regional characteristics.
Major risk factors identified in the cluster case analyses included living or working in high-risk areas, military service, and participation in outdoor or nighttime activities such as soccer, futsal, running, camping, short-term visit, and fishing. Similar findings have been reported internationally. For instance, increased exposure to mosquitoes was observed in southeastern Tanzania when religious and cultural activities were held outdoors from night until dawn, and an experimental study in Burkina Faso demonstrated that alcohol consumption heightened human attractiveness to mosquitoes [11,12]. Collectively, these findings suggest that both long-term exposures (through residence, occupation, or military service in high-risk areas) and short-term behavioral exposures (through nighttime outdoor activities, drinking, smoking, etc.) can significantly elevate the risk of malaria infection.
From a demographic standpoint, males accounted for 82.9% of the total number of cases, likely reflecting their greater involvement in outdoor-centered activities such as military service, fishing, sports, and farming than females. Regarding age distribution, cases were concentrated among individuals aged 20–50 years, who are more likely to engage in outdoor work or military service. These patterns highlight the need for targeted public health interventions based on both sex and age, emphasizing education and preventive practices for high-risk groups. Individuals in their 20s to 50s, in particular, should be encouraged to use mosquito repellents, wear protective clothing during prolonged outdoor activities, and recognize early symptoms of malaria for timely treatment. Such tailored approaches should be implemented at the community level to promote sustained prevention and lasting behavioral change.
Analysis of malaria incidence by region revealed that Gyeonggi accounted for over half of all cases despite a decrease in patient numbers. Notably, six of the nine high-case areas were located in Gyeonggi, underscoring the need for intensive malaria management in this region to achieve national eradication goals. In contrast, Seoul, Incheon, and Gangwon showed recent upward trends despite their relatively smaller case burdens. Therefore, the implementation of region-specific strategies is imperative. As malaria continues to occur throughout the metropolitan area, raising public awareness remains crucial. Healthcare providers in affected regions should also receive training and guidance to ensure the early diagnosis of malaria in febrile patients and the prompt use of rapid diagnostic testing.
To summarize, high-case areas should receive focused resources for prevention and control, whereas low-incidence areas should focus on education and community awareness to sustain nationwide malaria elimination efforts.
The Capital Regional Center for Disease Control and Prevention has strengthened its cluster case management system to support malaria elimination initiatives. According to the 2024 Malaria management guidelines, the definition of a cluster case was revised (reducing the interval between symptom onsets from 30 to 14 days) to enable faster surveillance and response. The Capital Regional Center for Disease Control and Prevention also participated in detailed epidemiological investigations through joint investigations with local health authorities. Since 2025, it has been working toward organizing comprehensive joint investigations for all cluster cases. These measures aim to prevent community transmission at an early stage and reinforce the foundation for malaria elimination efforts in high-incidence regions. The detailed epidemiological investigations of the 2024 cluster cases facilitated the identification of presumed infection sites and prompted the inspection of mosquito breeding habitats near patient residences. Targeted control measures, such as residual spraying, were also implemented. Furthermore, the scope of co-exposed individuals was defined to enable symptom monitoring, malaria testing, and prophylactic treatment. Education and outreach efforts were expanded for patients, their families, and local residents, focusing on communities where patients resided. Preventive education was delivered through community organizations such as neighborhood leaders and local meetings, as well as through healthcare providers and schools. Public awareness campaigns were further promoted via local media, posters, banners, and billboards to enhance outreach and engagement.
This study has some limitations. First, information on risk factors was collected through patient self-reports, which may be subject to recall bias and underreporting. Second, the revision of the 2024 Malaria management guidelines led to changes in the criteria for defining cluster cases, making direct comparisons with previous years difficult. In this study, cluster cases were defined as instances in which two or more patients were confirmed within a 14-day interval of symptom onset in a high-case area, with the distance between patient residences or presumed infection sites within 1 km. This definition was established for consistency in surveillance operations and practical applicability, considering the flight range of malaria vectors (approximately 1–10 km) and the need to strengthen prevention and control measures. However, this approach may not have fully captured actual epidemiological transmission links, and factors such as variation in incubation periods, population movement, and uncertainty in presumed infection sites may have led to over- or underestimation of cluster ranges. Moreover, parasite genotype concordance, which should ideally be considered when interpreting final results, was not included in the definition. Third, military-related cases lacked detailed information on base locations or training activities due to security constraints. Given the distinct living environments and exposure patterns in military populations compared with the general population, it is essential to establish a separate surveillance system and conduct in-depth analyses of exposure factors to develop targeted strategies that prevent reinfection and cluster outbreaks within military units.
Despite these limitations, this study provides valuable insights into malaria transmission patterns and cluster characteristics in the Seoul metropolitan area. It also offers foundational data to support the development of region-specific prevention and response strategies. Moving forward, it will be essential to further strengthen cluster case management, enhance risk-based public education, and promote personal protective practices, thereby contributing to the goal of re-eliminating malaria in ROK by 2030.
Acknowledgments
We would like to acknowledge HyunJung Kim for developing the dataset used for the 2024 malaria cluster-case analysis.
Declarations
Ethics Statement: Not applicable.
Funding Source: None.
Conflict of Interest: The authors have no conflicts of interest to declare.
Author Contributions: Conceptualization: KWH, MJK, YJS. Data curation: MJK, YJS. Formal analysis: MJK, YJS. Investigation: MJK, YJS. Methodology: KWH, MJK, YJS. Project administration: KWH. Resources: MJK, YJS. Supervision: KWH. Validation: MJK, YJS. Visualization: MJK, YJS. Writing – original draft: MJK, YJS. Writing – review & editing: KWH, HMK, MJK, YJS.
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